A tremendous amount of information and data is associated with the business of providing healthcare services and benefits. For example, there are as many benefits contracts as there are clients/consumers, and many different types of contracts, with different structures, elements, and requirements. Over time, the number and types of contracts continue to increase.
The amount, complexity, and dimensionality of the information and data make it challenging to explore the relationships between contracted benefits and their impact on business and operations. The daunting nature of this challenge prevents payers from running efficient benefits and claims processing systems. Furthermore, the complexity of such systems increases the training times for benefits coders, causes inconsistencies in the construction of benefits rules, increases the lead time to market for new products (new contracts), and makes it difficult to create innovative benefits products that adequately embrace the concept of consumerism in healthcare.
Conventionally, the analysis of existing contract data requires significant manual effort and the use of multiple spreadsheets. Significant manual effort is also needed to identify the correlation between the benefits structures across various contracts and to identify all contracts with a given benefit or benefits structure. Moreover, answering questions about current benefits structures is difficult and time-consuming.